scholarly journals Correction to: Automatic reconstruction of metabolic pathways from identified biosynthetic gene clusters

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Snorre Sulheim ◽  
Fredrik A. Fossheim ◽  
Alexander Wentzel ◽  
Eivind Almaas

An amendment to this paper has been published and can be accessed via the original article.

2020 ◽  
Author(s):  
Jacob L. Steenwyk ◽  
Matthew E. Mead ◽  
Sonja L. Knowles ◽  
Huzefa A. Raja ◽  
Christopher D. Roberts ◽  
...  

AbstractAspergillus fumigatus is a major human pathogen that causes hundreds of thousands of infections yearly with high mortality rates. In contrast, Aspergillus fischeri and the recently described Aspergillus oerlinghausenensis, the two species most closely related to A. fumigatus, are not known to be pathogenic. Some of the “cards of virulence” that A. fumigatus possesses are secondary metabolites that impair the host immune system, protect from host immune cell attacks, or acquire key nutrients. Secondary metabolites and the biosynthetic gene clusters (BGCs) that typically encode them often vary within and between fungal species. To gain insight into whether secondary metabolism-associated cards of virulence vary between A. fumigatus, A. oerlinghausenensis, and A. fischeri, we conducted extensive genomic and secondary metabolite profiling analyses. By analyzing multiple A. fumigatus, one A. oerlinghausenensis, and multiple A. fischeri strains, we identified both conserved and diverged secondary metabolism-associated cards of virulence. For example, we found that all species and strains examined biosynthesized the major virulence factor gliotoxin, consistent with the conservation of the gliotoxin BGC across genomes. However, species differed in their biosynthesis of fumagillin and pseurotin, both contributors to host tissue damage during invasive aspergillosis; these differences were reflected in sequence divergence of the intertwined fumagillin/pseurotin BGCs across genomes. These results delineate the similarities and differences in secondary metabolism-associated cards of virulence between a major fungal pathogen and its nonpathogenic closest relatives, shedding light into the genetic and phenotypic changes associated with the evolution of fungal pathogenicity.ImportanceThe major fungal pathogen Aspergillus fumigatus kills tens of thousands each year. In contrast, the two closest relatives of A. fumigatus, namely Aspergillus fischeri and Aspergillus oerlinghausenensis, are not considered pathogenic. A. fumigatus virulence stems, partly, from its ability to produce small molecules called secondary metabolites that have potent activities during infection. In this study, we examined whether A. fumigatus secondary metabolites and the metabolic pathways involved in their production are conserved in A. oerlinghausenensis and A. fischeri. We found that the nonpathogenic close relatives of A. fumigatus produce some, but not all, secondary metabolites thought to contribute to the success of A. fumigatus in causing human disease and that these similarities and differences were reflected in the underlying metabolic pathways involved in their biosynthesis. Compared to its nonpathogenic close relatives, A. fumigatus produces a distinct cocktail of secondary metabolites, which likely contributes to these organisms’ vastly different potentials to cause human disease. More broadly, the study of nonpathogenic organisms that have virulence-related traits, but are not currently considered agents of human disease, may facilitate the prediction of species capable of posing future threats to human health.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Snorre Sulheim ◽  
Fredrik A. Fossheim ◽  
Alexander Wentzel ◽  
Eivind Almaas

Abstract Background A wide range of bioactive compounds is produced by enzymes and enzymatic complexes encoded in biosynthetic gene clusters (BGCs). These BGCs can be identified and functionally annotated based on their DNA sequence. Candidates for further research and development may be prioritized based on properties such as their functional annotation, (dis)similarity to known BGCs, and bioactivity assays. Production of the target compound in the native strain is often not achievable, rendering heterologous expression in an optimized host strain as a promising alternative. Genome-scale metabolic models are frequently used to guide strain development, but large-scale incorporation and testing of heterologous production of complex natural products in this framework is hampered by the amount of manual work required to translate annotated BGCs to metabolic pathways. To this end, we have developed a pipeline for an automated reconstruction of BGC associated metabolic pathways responsible for the synthesis of non-ribosomal peptides and polyketides, two of the dominant classes of bioactive compounds. Results The developed pipeline correctly predicts 72.8% of the metabolic reactions in a detailed evaluation of 8 different BGCs comprising 228 functional domains. By introducing the reconstructed pathways into a genome-scale metabolic model we demonstrate that this level of accuracy is sufficient to make reliable in silico predictions with respect to production rate and gene knockout targets. Furthermore, we apply the pipeline to a large BGC database and reconstruct 943 metabolic pathways. We identify 17 enzymatic reactions using high-throughput assessment of potential knockout targets for increasing the production of any of the associated compounds. However, the targets only provide a relative increase of up to 6% compared to wild-type production rates. Conclusion With this pipeline we pave the way for an extended use of genome-scale metabolic models in strain design of heterologous expression hosts. In this context, we identified generic knockout targets for the increased production of heterologous compounds. However, as the predicted increase is minor for any of the single-reaction knockout targets, these results indicate that more sophisticated strain-engineering strategies are necessary for the development of efficient BGC expression hosts.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bahar Behsaz ◽  
Edna Bode ◽  
Alexey Gurevich ◽  
Yan-Ni Shi ◽  
Florian Grundmann ◽  
...  

AbstractNon-Ribosomal Peptides (NRPs) represent a biomedically important class of natural products that include a multitude of antibiotics and other clinically used drugs. NRPs are not directly encoded in the genome but are instead produced by metabolic pathways encoded by biosynthetic gene clusters (BGCs). Since the existing genome mining tools predict many putative NRPs synthesized by a given BGC, it remains unclear which of these putative NRPs are correct and how to identify post-assembly modifications of amino acids in these NRPs in a blind mode, without knowing which modifications exist in the sample. To address this challenge, here we report NRPminer, a modification-tolerant tool for NRP discovery from large (meta)genomic and mass spectrometry datasets. We show that NRPminer is able to identify many NRPs from different environments, including four previously unreported NRP families from soil-associated microbes and NRPs from human microbiota. Furthermore, in this work we demonstrate the anti-parasitic activities and the structure of two of these NRP families using direct bioactivity screening and nuclear magnetic resonance spectrometry, illustrating the power of NRPminer for discovering bioactive NRPs.


Author(s):  
Noraziah M. Zin ◽  
Aishah Ismail ◽  
David R. Mark ◽  
Gareth Westrop ◽  
Jana K. Schniete ◽  
...  

Endophytic actinobacteria offer great potential as a source of novel bioactive compounds. In order to investigate the potential for the production of secondary metabolites by endophytes, we recovered a filamentous microorgansism from the tree Antidesma neurocarpum Miq. After phenotypic analysis and whole genome sequencing we demonstrated that this organism, SUK42 was a member of the actinobacterial genus Kitasatospora. This strain has a small genome in comparison with other type strains of this genus and has lost metabolic pathways associated with Stress Response, Nitrogen Metabolism and Secondary Metabolism. Despite this SUK42 can grow well in a laboratory environment and encodes a core genome that is consistent with other members of the genus. Finally, in contrast to other members of Kitasatospora, SUK42 encodes saccharide secondary metabolite biosynthetic gene clusters, one of which with similarity to the acarviostatin cluster, the product of which displays α-amylase inhibitory activity. As extracts of the host plant demonstrate this inhibitory activity, it suggests that the potential medicinal properties of A. neurocarpum Miq might be provided by the endophytic partner and illustrate the potential for exploitation of endophytes for clinical or industrial uses.


2020 ◽  
Author(s):  
Snorre Sulheim ◽  
Fredrik A. Fossheim ◽  
Alexander Wentzel ◽  
Eivind Almaas

AbstractBackgroundA wide range of bioactive compounds are produced by enzymes and enzymatic complexes encoded in biosynthetic gene clusters (BGCs). These BGCs can be identified and functionally annotated based on their DNA sequence. Candidates for further research and development may be prioritized based on properties such as their functional annotation, (dis)similarity to known BGCs, and bioactivity assays. Production of the target compound in the native strain is often not achievable, rendering heterologous expression in an optimized host strain as a promising alternative. Genome-scale metabolic models are frequently used to guide strain development, but large-scale incorporation and testing of heterologous production of complex natural products in this framework is hampered by the amount of manual work required to translate annotated BGCs to metabolic pathways. To this end, we have developed a pipeline for an automated reconstruction of BGC associated metabolic pathways responsible for the synthesis of non-ribosomal peptides and polyketides, two of the dominant classes of bioactive compounds.ResultsThe developed pipeline correctly predicts 72.8% of the metabolic reactions in a detailed evaluation of 8 different BGCs comprising 228 functional domains. By introducing the reconstructed pathways into a genome-scale metabolic model we demonstrate that this level of accuracy is sufficient to make reliable in silico predictions with respect to production rate and gene knockout targets. Furthermore, we apply the pipeline to a large BGC database and reconstruct 943 metabolic pathways. We identify 17 enzymatic reactions using high-throughput assessment of potential knockout targets for increasing the production of any of the associated compounds. However, the targets only provide a relative increase of up to 6% compared to wild-type production rates.ConclusionsWith this pipeline we pave the way for an extended use of genome-scale metabolic models in strain design of heterologous expression hosts. In this context, we identified generic knockout targets for the increased production of heterologous compounds. However, as the predicted increase is minor for any of the single-reaction knockout targets, these results indicate that more sophisticated strain-engineering strategies are necessary for the development of efficient BGC expression hosts.


Author(s):  
Patrick Videau ◽  
Kaitlyn Wells ◽  
Arun Singh ◽  
Jessie Eiting ◽  
Philip Proteau ◽  
...  

Cyanobacteria are prolific producers of natural products and genome mining has shown that many orphan biosynthetic gene clusters can be found in sequenced cyanobacterial genomes. New tools and methodologies are required to investigate these biosynthetic gene clusters and here we present the use of <i>Anabaena </i>sp. strain PCC 7120 as a host for combinatorial biosynthesis of natural products using the indolactam natural products (lyngbyatoxin A, pendolmycin, and teleocidin B-4) as a test case. We were able to successfully produce all three compounds using codon optimized genes from Actinobacteria. We also introduce a new plasmid backbone based on the native <i>Anabaena</i>7120 plasmid pCC7120ζ and show that production of teleocidin B-4 can be accomplished using a two-plasmid system, which can be introduced by co-conjugation.


eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Zachary Charlop-Powers ◽  
Jeremy G Owen ◽  
Boojala Vijay B Reddy ◽  
Melinda A Ternei ◽  
Denise O Guimarães ◽  
...  

Recent bacterial (meta)genome sequencing efforts suggest the existence of an enormous untapped reservoir of natural-product-encoding biosynthetic gene clusters in the environment. Here we use the pyro-sequencing of PCR amplicons derived from both nonribosomal peptide adenylation domains and polyketide ketosynthase domains to compare biosynthetic diversity in soil microbiomes from around the globe. We see large differences in domain populations from all except the most proximal and biome-similar samples, suggesting that most microbiomes will encode largely distinct collections of bacterial secondary metabolites. Our data indicate a correlation between two factors, geographic distance and biome-type, and the biosynthetic diversity found in soil environments. By assigning reads to known gene clusters we identify hotspots of biomedically relevant biosynthetic diversity. These observations not only provide new insights into the natural world, they also provide a road map for guiding future natural products discovery efforts.


2021 ◽  
Author(s):  
Xuhua Mo ◽  
Tobias A. M. Gulder

Over 30 biosynthetic gene clusters for natural tetramate have been identified. This highlight reviews the biosynthetic strategies for formation of tetramic acid unit for the first time, discussing the individual molecular mechanism in detail.


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